3 papers
stat.ME2024
Using a Two-Parameter Sensitivity Analysis Framework to Efficiently Combine Randomized and Non-randomized Studies
Ruoqi Yu, Bikram Karmakar, Jessica Vandeleest +1
Causal inference is vital for informed decision-making across fields such as biomedical research and social sciences. Randomized controlled trials (RCTs) are considered the gold st…
stat.ME2024
Re-evaluating the impact of hormone replacement therapy on heart disease using match-adaptive randomization inference
Samuel D. Pimentel, Ruoqi Yu
Matching is an appealing way to design observational studies because it mimics the data structure produced by stratified randomized trials, pairing treated individuals with similar…
stat.ME2023
Balancing Weights for Causal Inference in Observational Factorial Studies
Ruoqi Yu, Peng Ding
Many scientific questions in biomedical, environmental, and psychological research involve understanding the effects of multiple factors on outcomes. While factorial experiments ar…